77 citations · 131 across the 21 of their papers we have counts for
9 papers · 1 filter
GShield: Mitigating Poisoning Attacks in Federated Learning
Sameera K. M., Serena Nicolazzo, Antonino Nocera +2
Federated Learning (FL) has recently emerged as a revolutionary approach to collaborative training Machine Learning models. In particular, it enables decentralized model training w…
Protecting Deep Neural Network Intellectual Property with Chaos-Based White-Box Watermarking
Sangeeth B, Serena Nicolazzo, Deepa K. +1
The rapid proliferation of deep neural networks (DNNs) across several domains has led to increasing concerns regarding intellectual property (IP) protection and model misuse. Train…
CTI Dataset Construction from Telegram
Dincy R. Arikkat, Sneha B. T., Serena Nicolazzo +4
Cyber Threat Intelligence (CTI) enables organizations to anticipate, detect, and mitigate evolving cyber threats. Its effectiveness depends on high-quality datasets, which support…
Enhancing Android Malware Detection with Retrieval-Augmented Generation
Saraga S., Anagha M. S., Dincy R. Arikkat +4
The widespread use of Android applications has made them a prime target for cyberattacks, significantly increasing the risk of malware that threatens user privacy, security, and de…
Security through the Eyes of AI: How Visualization is Shaping Malware Detection
Matteo Brosolo, Asmitha K. A., Mauro Conti +5
Malware, a persistent cybersecurity threat, increasingly targets interconnected digital systems such as desktop, mobile, and IoT platforms through sophisticated attack vectors. By…
DroidTTP: Mapping Android Applications with TTP for Cyber Threat Intelligence
Dincy R Arikkat, Vinod P., Rafidha Rehiman K. A. +4
The widespread adoption of Android devices for sensitive operations like banking and communication has made them prime targets for cyber threats, particularly Advanced Persistent T…
Secure Federated Data Distillation
Marco Arazzi, Mert Cihangiroglu, Serena Nicolazzo +1
Dataset Distillation (DD) is a powerful technique for reducing large datasets into compact, representative synthetic datasets, accelerating Machine Learning training. However, trad…
How Secure is Forgetting? Linking Machine Unlearning to Machine Learning Attacks
Muhammed Shafi K. P., Serena Nicolazzo, Antonino Nocera +1
As Machine Learning (ML) evolves, the complexity and sophistication of security threats against this paradigm continue to grow as well, threatening data privacy and model integrity…
Augmented Knowledge Graph Querying leveraging LLMs
Marco Arazzi, Davide Ligari, Serena Nicolazzo +1
Adopting Knowledge Graphs (KGs) as a structured, semantic-oriented, data representation model has significantly improved data integration, reasoning, and querying capabilities acro…